A role for qualitative methods in researching Twitter data on a popular science article's communication
Big Data communication researchers have highlighted the need for qualitative analysis of online science conversations to better understand their meaning. However, a scholarly gap exists in exploring how qualitative methods can be applied to small data regarding micro-bloggers' communications ab...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Research Metrics and Analytics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/frma.2024.1431298/full |
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| author | Travis Noakes Corrie Susanna Uys Patricia Ann Harpur Izak van Zyl |
| author_facet | Travis Noakes Corrie Susanna Uys Patricia Ann Harpur Izak van Zyl |
| author_sort | Travis Noakes |
| collection | DOAJ |
| description | Big Data communication researchers have highlighted the need for qualitative analysis of online science conversations to better understand their meaning. However, a scholarly gap exists in exploring how qualitative methods can be applied to small data regarding micro-bloggers' communications about science articles. While social media attention assists with article dissemination, qualitative research into the associated microblogging practices remains limited. To address these gaps, this study explores how qualitative analysis can enhance science communication studies on microblogging articles. Calls for such qualitative approaches are supported by a practical example: an interdisciplinary team applied mixed methods to better understand the promotion of an unorthodox but popular science article on Twitter over a 2-year period. While Big Data studies typically identify patterns in microbloggers' activities from large data sets, this study demonstrates the value of integrating qualitative analysis to deepen understanding of these interactions. In this study, a small data set was analyzed using NVivo™ by a pragmatist and MAXQDA™ by a statistician. The pragmatist's multimodal content analysis found that health professionals shared links to the article, with its popularity tied to its role as a communication event within a longstanding debate in the health sciences. Dissident professionals used this article to support an emergent paradigm. The analysis also uncovered practices, such as language localization, where a title was translated from English to Spanish to reach broader audiences. A semantic network analysis confirmed that terms used by the article's tweeters strongly aligned with its content, and the discussion was notably pro-social. Meta-inferences were then drawn by integrating the findings from the two methods. These flagged the significance of contextualizing the sharing of a health science article in relation to tweeters' professional identities and their stances on health-related issues. In addition, meta-critiques highlighted challenges in preparing accurate tweet data and analyzing them using qualitative data analysis software. These findings highlight the valuable contributions that qualitative research can make to research involving microblogging data in science communication. Future research could critique this approach or further explore the microblogging of key articles within important scientific debates. |
| format | Article |
| id | doaj-art-d967eff52c924e678718ee6eafeeaeb9 |
| institution | Kabale University |
| issn | 2504-0537 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Research Metrics and Analytics |
| spelling | doaj-art-d967eff52c924e678718ee6eafeeaeb92025-01-07T06:44:46ZengFrontiers Media S.A.Frontiers in Research Metrics and Analytics2504-05372025-01-01910.3389/frma.2024.14312981431298A role for qualitative methods in researching Twitter data on a popular science article's communicationTravis Noakes0Corrie Susanna Uys1Patricia Ann Harpur2Izak van Zyl3Faculty of Health and Wellness Sciences, Cape Peninsula University of Technology, Cape Town, South AfricaApplied Microbial and Health Biotechnology Institute, Cape Peninsula University of Technology, Cape Town, South AfricaDepartment of Information Technology, Faculty of Informatics and Design, Cape Peninsula University of Technology, Cape Town, South AfricaCentre for Postgraduate Studies, Cape Peninsula University of Technology, Cape Town, South AfricaBig Data communication researchers have highlighted the need for qualitative analysis of online science conversations to better understand their meaning. However, a scholarly gap exists in exploring how qualitative methods can be applied to small data regarding micro-bloggers' communications about science articles. While social media attention assists with article dissemination, qualitative research into the associated microblogging practices remains limited. To address these gaps, this study explores how qualitative analysis can enhance science communication studies on microblogging articles. Calls for such qualitative approaches are supported by a practical example: an interdisciplinary team applied mixed methods to better understand the promotion of an unorthodox but popular science article on Twitter over a 2-year period. While Big Data studies typically identify patterns in microbloggers' activities from large data sets, this study demonstrates the value of integrating qualitative analysis to deepen understanding of these interactions. In this study, a small data set was analyzed using NVivo™ by a pragmatist and MAXQDA™ by a statistician. The pragmatist's multimodal content analysis found that health professionals shared links to the article, with its popularity tied to its role as a communication event within a longstanding debate in the health sciences. Dissident professionals used this article to support an emergent paradigm. The analysis also uncovered practices, such as language localization, where a title was translated from English to Spanish to reach broader audiences. A semantic network analysis confirmed that terms used by the article's tweeters strongly aligned with its content, and the discussion was notably pro-social. Meta-inferences were then drawn by integrating the findings from the two methods. These flagged the significance of contextualizing the sharing of a health science article in relation to tweeters' professional identities and their stances on health-related issues. In addition, meta-critiques highlighted challenges in preparing accurate tweet data and analyzing them using qualitative data analysis software. These findings highlight the valuable contributions that qualitative research can make to research involving microblogging data in science communication. Future research could critique this approach or further explore the microblogging of key articles within important scientific debates.https://www.frontiersin.org/articles/10.3389/frma.2024.1431298/fullcontent analysisdebate about health sciencemicroblogging datamultimodal content analysisresearch methodsemantic network analysis |
| spellingShingle | Travis Noakes Corrie Susanna Uys Patricia Ann Harpur Izak van Zyl A role for qualitative methods in researching Twitter data on a popular science article's communication Frontiers in Research Metrics and Analytics content analysis debate about health science microblogging data multimodal content analysis research method semantic network analysis |
| title | A role for qualitative methods in researching Twitter data on a popular science article's communication |
| title_full | A role for qualitative methods in researching Twitter data on a popular science article's communication |
| title_fullStr | A role for qualitative methods in researching Twitter data on a popular science article's communication |
| title_full_unstemmed | A role for qualitative methods in researching Twitter data on a popular science article's communication |
| title_short | A role for qualitative methods in researching Twitter data on a popular science article's communication |
| title_sort | role for qualitative methods in researching twitter data on a popular science article s communication |
| topic | content analysis debate about health science microblogging data multimodal content analysis research method semantic network analysis |
| url | https://www.frontiersin.org/articles/10.3389/frma.2024.1431298/full |
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